Cogniify

United States
Year Founded: 2025

Jobs at Cogniify

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Recently posted jobs

8 Hours AgoSaved
In-Office
2 Locations
Artificial Intelligence • Information Technology • Machine Learning • Consulting
Lead design, development, and production deployment of scalable ML systems across domains. Own end-to-end ML lifecycle, architect pipelines and serving, drive MLOps maturity, mentor engineers, conduct design/code reviews, and ensure monitoring, governance, and model reliability in production.
22 Hours AgoSaved
In-Office
6 Locations
Artificial Intelligence • Information Technology • Machine Learning • Consulting
Design, build, and deploy ML models and end-to-end pipelines; implement MLOps practices; deploy containers to cloud production; monitor model performance and drift; collaborate with engineers and product teams; optimize latency and throughput; write production-quality code and mentor junior engineers.
22 Hours AgoSaved
In-Office
5 Locations
Artificial Intelligence • Information Technology • Machine Learning • Consulting
Design, build, and maintain production-grade ETL/ELT pipelines and data models using dbt, Spark, and cloud platforms. Manage ingestion, data quality, observability, semantic layers, and BI outputs. Collaborate with analysts and data scientists to deliver governed, high-quality data products and implement DataOps and CI/CD practices.
22 Hours AgoSaved
In-Office
5 Locations
Artificial Intelligence • Information Technology • Machine Learning • Consulting
Lead technical vision and architecture for enterprise ML platforms and MLOps. Design training, feature, serving, and observability systems; establish ML lifecycle and governance; solve complex cross-team engineering problems; mentor senior engineers; evaluate emerging AI technologies; drive cost optimization, compliance, and organizational alignment.
8 Hours AgoSaved
Remote
United States
Artificial Intelligence • Information Technology • Machine Learning • Consulting
Lead end-to-end client AI transformation engagements: discover and frame executive problems, design and build production-credible PoAs (data pipelines, integrations, LLM/RAG apps) within 2–3 weeks, present to executives, hand off to delivery, mentor junior FDEs, and convert PoAs into full engagements.